Virtual Space Vertex Storage Compression
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Solution Overview
Problem
The storage requirements for virtual spaces are substantial due to the need to store extensive information defining virtual objects, topography, and user-generated content, which burdens host servers, runtime memory, and removable storage, especially when using conventional electronic storage methods that rely on floating-point formats for numerical values.
Innovation Solution
A system that reduces storage requirements by normalizing and converting floating-point values into integer representations, allowing for more efficient encoding and storage of vertex position information in virtual spaces, utilizing a combination of normalization, conversion, and storage components to compress data without loss of precision.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If floating-point format is used to store vertex position information, then measurement precision is maintained, but storage space increases substantially
Solution Approach 1:
The patent changes the data format parameter from floating-point to normalized integer representation. Vertex positions are stored as normalized integers where the actual position is reconstructed by multiplying with a scale factor during rendering. This parameter change maintains positional precision while reducing storage requirements from typical 32-bit or 64-bit floating-point values to compact integer formats.
Solution Approach 2:
The patent introduces a scale factor dimension that separates the storage representation from the actual coordinate values. Instead of storing absolute floating-point coordinates, the system stores normalized integer values and applies the scale factor during runtime to reconstruct the original positions, effectively adding a computational dimension to the storage model.
2Reliability
If conventional electronic storage methods are used, then data integrity is maintained, but storage burden increases on host servers and runtime memory
Solution Approach 1:
The patent changes the storage parameter from conventional floating-point format to normalized integer format with an associated scale factor. This transformation maintains data integrity because the normalized integers can be perfectly converted back to original floating-point values through multiplication with the scale factor, while significantly reducing the storage burden on host servers and runtime memory.
3Adaptability or versatility
If user-generated content is continuously added to virtual space, then adaptability increases, but storage requirements grow substantially
Solution Approach 1:
The patent applies parameter change by storing user-generated content coordinates in normalized integer format rather than floating-point format. As users continuously add content to the virtual space, this storage method maintains adaptability and content flexibility while preventing substantial growth in storage requirements through efficient encoding of position data.
Data Source
AI summary
Systems and methods of reducing storage requirements for storing information defining a virtual space are presented herein. In particular, a compressed format of information defining a virtual space may be generated. The virtual space may include virtual space content modeled as polygons. An individual polygon may be defined by an individual set of vertices. The information defining the virtual space may include vertex position information, and/or other information. The vertex position information may comprise individual positions of individual vertices of individual polygons represented as vectors having vector components.